Capital One Patente

A method and related system for reducing computational cost when using a natural language model for adaptive forms includes transcribing an utterance produced into a text portion during a conversation associated with a first person. The method also includes determining a result indicating that an interval indicating when a field of the set of data entry fields was last updated satisfies a data entry interval threshold. The method also includes providing the text portion to a natural language model to predict a set of intents based on the result and presenting at least one element of the second set of UI elements on the UI screen based on the set of intents.

Aspects of this disclosure relate to systems and methods for preventing injection attacks to large language models (LLMs). Techniques implemented by these systems and methods can include obtaining a query from a user device that is configured to cause an LLM to generate an output outside of a predetermined scope. In response to obtaining the query, systems can execute one or more evaluation models that are configured to identify one or more compatibility issues that can arise if the queries are executed by an LLM. Where a query is identified as having one compatibility issue(s), the systems described herein can either update the query to address the issue. Additionally, or alternatively, the systems described herein can prevent the processing of the query (and processing in furtherance of the injection attack) by an LLM.

Described herein are systems, methods, and programming for determining network resource code updates in real time while also reducing network resource consumption used to determine performance impacts of the network resource code updates. Updates to code portions may be generated and evaluated in a secure virtual computing space for an event of a sequence of events. If the updates to the code portions satisfy processing conditions, other events from the sequence may be evaluated against the same updates. A retroactive analysis of a portfolio of authorized accounts, each including a respective sequence of events, may be analyzed to determine the impact of the network resource code updates to the portfolio.

A system for improving scalability of machine learning may identify a machine learning libraries that are to be used for an execution of a serverless machine learning process using a serverless service provided by a cloud computing platform; remove a plurality of portions of one or more first libraries, of the machine learning libraries, that are to be pre-loaded into the serverless service; select one or more second libraries, of the machine learning libraries, that are to be dynamically loaded while the serverless machine learning process is executing; determine smart sampling of data to be used for the serverless machine learning process; and cause the execution of the serverless machine learning process by uploading a package that includes the one or more first libraries to the serverless service, causing the one or more second libraries to be dynamically loaded, and using the portion of the data.

Exemplary embodiments may use a contactless card as a secondary form of authentication in a multi-factor authentication for a secure messaging service. The recipient party of a request to initiate a messaging service session (such as a server computing device) may be programmed to use the phone number of the originating device to look up records regarding an identity of a party and their associated phone number as a primary credential and then may require an authentication credential originating from the contactless card as a secondary credential for the initiating party. In some instances, the credential originating from the contactless card is a onetime password that is valid only for a period of time. The recipient party determines whether the onetime password is valid. If both credentials are valid, a secure messaging session may be initiated with the initiating party.

In some implementations, a remote scanning system may receive, from a developer system, a request for a software package from a package repository. The remote scanning system may provide at least a portion of the software package to a machine learning model in order to receive a security indicator associated with the software package. The remote scanning system may generate a message based on the security indicator. The remote scanning system may transmit, to the developer system and in response to the request, the message. The remote scanning system may receive, from the developer system, a confirmation that the software package is requested. The remote scanning system may forward the software package from the package repository and to the developer system.

In some implementations, a system may receive, from a client device, a client request for a dynamic user experience associated with a user interface, wherein the client request indicates client data associated with the client device. The system may obtain, based on the client data, dynamic data associated with the dynamic user experience and the client device. The system may provide, to a tile utility component of the system, tile definition information, wherein the tile definition information includes the client data, an indication of the dynamic user experience, and the dynamic data. The system may obtain, from the tile utility component, the one or more tile specifications based on the tile definition information. The system may transmit, to the client device, the one or more tile specifications to cause the client device to display the dynamic user experience via the user interface.

In some implementations, a system may receive, from a client device, a request for a dynamic user experience associated with a user interface. The system may receive, from the client device and in association with receiving the request for the dynamic user experience, capability information indicating one or more client capabilities supported by the client device for the dynamic user interface tiles. The system may transmit, to the client device, a tile specification indicating user interface information for a user interface tile associated with the dynamic user experience, where the tile specification is in accordance with the capability information and one or more provider capabilities.

Various examples generally directed to unlocking a locked contactless card for use as payment in card-present transactions are provided. The contactless card is a payment card associated with a payment account. An application executing on a mobile device may be operable to enable unlocking the locked contactless card and receive an indication that the contactless card associated with the mobile device is unlocked for use in card-present transactions. The application may present information related to permitted uses of the unlocked contactless card via a graphical user interface. The permitted uses of the unlocked contactless card may be modified via the graphical user interface.

In some implementations, a system may receive, from a client device, a client request for a dynamic user experience associated with a user interface. The system may obtain an experience configuration associated with the dynamic user experience, wherein the experience configuration indicates a data provider for the dynamic user experience. The system may transmit, to the data provider, a data request, wherein the data request is generated based on the experience configuration. The system may receive, from the data provider, the dynamic data based on transmitting the data request. The system may transmit, to the client device, one or more tile specifications indicating user interface information for a user interface tile associated with the dynamic user experience to cause the client device to display the user interface tile via the user interface.

Aspects discussed herein may relate to methods and techniques for scanning application programming interface requests and responses to more readily identify data issues. The system may aggregate one or more data requests and/or responses according to correlated data transactions between devices. The system may then analyze traffic associated with those requests to determine if the responses are consistent with data policies. If a response is out of line with such policies, a system for reporting and correction are described.

The present disclosure relates to systems and methods for using multicomputer data transferring to active contactless communication. In one example, such a system may include at least one memory storing instructions and at least one processor configured to execute the instructions to perform one or more operations, the operations including: receiving a transaction associated with a merchant on a list of merchants stored in the at least one memory; determining, based on the merchant, a remote server associated with the merchant; assembling a data packet including an identifier of the contactless card and an identifier of the transaction; transmitting the data packet to the determined server across one or more computer networks; receiving confirmation from the determined sever in response to the data packet; and transmitting the confirmation to a user device associated with the transaction.

Methods and systems disclosed herein describe tokenizing data to generate a secure token that is limited in scope (e.g., directed to a specific recipient) and limited in time (e.g., valid for only a specified period of time). A detokenization process may be employed to recover encrypted data of the secure token without the need for any relational database lookup processes, thereby reducing cost while maintaining robust protection against unintended recipients that attempt to recover the encrypted data.

Example embodiments of systems and methods for data transmission and authorizing transactions between transmitting and receiving devices are provided. In an embodiment, a method includes generating a request for at least one authentication factor when a value of the transaction exceeds a predetermined value, wherein the at least one authentication factor includes a cryptogram, receiving an authentication signal, the authentication signal including the cryptogram, and authorizing a transaction when the authentication signal is received.

Various embodiments are generally directed to techniques for generating rules automatically navigate a website and perform updates of payment token information.

Systems and methods are disclosed for responding to a data incident. One or more processors receive one or more indicators of a data leak occurring at one or more nodes of a network. One or more processors causes an identification, by a machine-learning model, of one or more compromised nodes within the network based on the one or more indicators of a data leak. One or more processors may receive from the machine-learning model the identification of the one or more compromised nodes. One or more processors modify access permissions at one or more identified compromised nodes based on a user permission schema or pre-determined access rules, in response to the data leak. One or more processors cause a generation of a notification regarding the data leak and the modifications of access permissions to one or more users associated with the network.

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